A large amount of infrastructure data (e.g. relating to a network of pipes) exists. For example, this infrastructure data may include information regarding various conditions of the pipes, locations of the pipes within a network, methods of repairing, cleaning, or replacing the pipes, costs associated therewith, maintenance schedules, and the like.
There are many contexts in which a condition of a pipe is of importance. For example, every year, wastewater managers must make decisions about which portions of their collection system should be maintained, rehabilitated or replaced. The Environmental Protection Agency (EPA) and American Society of Civil Engineers (ASCE) both project hundreds of billions of dollars of investment shortfalls facing aging wastewater infrastructure. Thus, it is important that wastewater managers are able to spend their limited funds most wisely to reduce risks and maintain service levels at a low cost.
In the example context of managing a municipal wastewater collection system, a wastewater manager faced with a limited budget makes prioritization and investment decisions based on the best information available at the time. Unfortunately, although a large amount of information may be available, this information is often difficult to access and analyze and thus is often unusable. This is due to lack of adequate technology for providing accurate representations of the condition of the pipe sections making up the collection system and the absence of systems and methods for organizing and analyzing the infrastructure data.